Neural Mechanisms Supporting Implicit and Explicit Sensorimotor Learning

支持内隐和外显感觉运动学习的神经机制

• 批准号: 10387283
• 负责人: Jonathan Tsay
• 金额: $ 4.29万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10387283
• 关键词: Address; Basal Ganglia; Basic Science; Behavior; Behavior Control; Behavioral; Brain; Cerebellum; Clinical; Closure by clamp; Competence; Complement; Computer Models; Conceptions; Cues; Delaware; Dissociation; Doctor of Philosophy; Environment; Evaluation; Exhibits; Faculty; Fatigue; Feedback; Foundations; Future; Goals; Grain; Human; Impairment; Individual; Injury; Institution; Intervention; Learning; Link; Literature; Memory; Mentors; Mentorship; Methods; Mind; Modeling; Motor; Movement; Muscle Fatigue; National Research Service Awards; Neurologist; Neuropsychology; Parkinson Disease; Participant; Patients; Pattern; Physiological; Play; Positioning Attribute; Postdoctoral Fellow; Process; Rehabilitation therapy; Reporting; Research; Retrieval; Rewards; Rodent Model; Role; Savings; Signal Transduction; Solid; Spinocerebellar Ataxias; Strategic Planning; Structure; Supervision; Support System; System; Testing; Training; Volition; Walking; Work; Writing; analytical tool; base; behavioral study; brain machine interface; cognitive neuroscience; cognitive rehabilitation; design; experimental study; flexibility; improved; insight; motor control; motor learning; nervous system disorder; neuroimaging; neuromechanism; nonhuman primate; novel; novel strategies; operation; pedagogy; physical therapist; power analysis; professor; recruit; relating to nervous system; reward processing; sensorimotor system; skills; success; therapy design

TITLE of PROJECT Neural Mechanisms Supporting Implicit and Explicit Sensorimotor Learning PROJECT SUMMARY Successful goal-directed actions require a flexible motor control system, one that can quickly respond to changes in the body (e.g., muscle fatigue) and in the environment (e.g., a windy day). Such flexibility depends on the operation of multiple learning processes. Implicit learning processes (i.e., implicit adaptation) keep the sensorimotor system exquisitely calibrated in an automatic manner, whereas explicit learning processes can facilitate rapid adjustments in a strategic, yet effortful manner. While the cerebellum and basal ganglia are prominently featured in the motor learning literature, their contribution to sensorimotor adaptation remains unclear, in part because past studies have employed tasks that conflate implicit and explicit learning processes. To disentangle the specific contributions of the cerebellum and basal ganglia to sensorimotor adaptation, I will use a set of behavioral tasks developed in my mentor’s lab that are designed to isolate the contribution of different learning processes. The results from this work have revised our current computational understanding of sensorimotor adaptation and have set the stage for taking a new look at the subcortical systems involved in this form of learning. In the proposed studies, we will test patients with spinocerebellar ataxia (SCA) and Parkinson’s disease (PD) on these tasks. In terms of basic research, the results will be important in advancing our understanding of how distributed neural systems support motor learning. In terms of translational benefit, the insights from this work will aid physical therapists to better tailor interventions that tap into intact learning mechanisms or enhance impaired ones. This NRSA F31 training plan encompasses two specific aims (three experiments) that will be conducted at UC Berkeley under the supervision of my sponsor, Prof. Richard Ivry. As a PI for 30 years, Prof. Ivry has trained 24 Ph.D. trainees and 21 post-doc fellows, many of whom hold faculty positions at research institutions. Under the supervision of Prof. Ivry, this proposal outlines a comprehensive training plan, centered on gaining fluency in computational modeling of behavior, methods in neuropsychology, writing and grantsmanship, presenting and disseminating research, and clinical pedagogy and mentorship. I will benefit from frequent interactions with Prof. Hyosub Kim, a former post-doc with Prof. Ivry who is now an Assistant Professor at the Univ. of Delaware. Prof. Kim provides added expertise in computational modeling and mentorship as a trained physical therapist. I will also benefit from mentorship provided by Prof. Robert Knight, a Professor and neurologist at UC Berkeley, who can provide additional training in patient evaluation and general training drawing from many years of stellar neuropsychological research with many patient groups and trainees. In summary, this training plan will build a solid foundation for my future role as a PI, working at the intersection of cognitive neuroscience and rehabilitation.

项目名称 支持内隐和外显感觉运动学习的神经机制 项目摘要 成功的目标导向行动需要一个灵活的运动控制系统，一个可以快速响应变化的系统 在体内（例如，肌肉疲劳）和在环境中（例如，有风的日子）。这种灵活性取决于 多个学习过程的操作。内隐学习过程（implicit learning processes）隐式适应）保持 感觉运动系统以自动方式精确校准，而外显学习过程可以 以战略性但有效的方式促进快速调整。而小脑和基底神经节 在运动学习文献中，它们的突出特点是对感觉运动适应的贡献仍然存在。 不清楚，部分原因是过去的研究采用了将内隐和外显学习过程混为一谈的任务。 为了解开小脑和基底神经节对感觉运动适应的特殊贡献，我将 我使用了一组在我导师的实验室里开发的行为任务，这些任务旨在隔离不同行为的贡献。 学习过程。这项工作的结果已经修订了我们目前的计算理解， 感觉运动适应，并为重新审视参与这一过程的皮层下系统奠定了基础。 学习的形式。在拟议的研究中，我们将测试脊髓小脑性共济失调（SCA）和帕金森氏症患者 疾病（PD）在这些任务。在基础研究方面，这些结果将对推进我们的 了解分布式神经系统如何支持运动学习。在翻译效益方面， 这项工作的见解将有助于物理治疗师更好地调整干预措施，利用完整的学习 机制或增强受损的机制。 这个NRSA F31培训计划包括两个具体目标（三个实验），将在加州大学进行 伯克利分校在我的赞助商理查德·伊夫里教授的监督下。作为一名PI 30年来，Ivry教授已经培训了24名 博士研究生和21名博士后研究员，其中许多人在研究机构担任教职。下 在Ivry教授的监督下，该建议概述了一个全面的培训计划，以获得流利的英语为中心， 行为的计算建模，神经心理学方法，写作和语法，演示和 传播研究、临床教学法和指导。我将受益于与教授的频繁互动。 Hyosub Kim，Ivry教授的前博士后，现在是特拉华州大学的助理教授。教授 Kim作为一名训练有素的物理治疗师提供了计算建模和指导方面的额外专业知识。我会 我也受益于加州大学伯克利分校教授和神经学家罗伯特·奈特教授提供的指导， 可以提供额外的培训，在病人的评估和一般培训借鉴多年的恒星 神经心理学研究与许多患者群体和学员。总之，本培训计划将建立一个 为我未来作为一名PI的角色奠定了坚实的基础，在认知神经科学和康复的交叉点工作。